Essays on the Economics of Social Networks

This dissertation consists of two projects, both concerned with how social networks form and how they affect economic decisions. In the first project, entitled Identifying Influential Agents in a Social Network, I define influence centrality, a new measure of influence which combines information on node and neighbor characteristics as well as information on the network structure, by building a model of friendship formation and peer effects and calculating the change in the equilibrium behavior of the network when one node changes its behavior. I apply the model to the context of smoking among middle and high school students and show that a targeted anti-smoking intervention in which a small number of influential smoking students are treated may be more efficient than a uniform program where every student in the school receives the same anti-smoking treatment. The second project, entitled Quantifying Spillovers in Network Formation Over Time, is a joint work with Sean Chu and Shankar Kalyanaraman at Facebook. The goal of the project is to separately identify and understand the relative importance of network effects and unobserved heterogeneity in a multi-period network formation model. Here, we define network effects to be the effect of the number of mutual friends on the probability of friendship and assume that unobserved heterogeneity is time-consistent. We estimate the model on a de-identified panel data set from a small group of users on Facebook and find that both network effects and unobserved heterogeneity are statistically and economically significant predictors of friendship formation on Facebook. We further re-estimate the model first, without network effects and next, without unobserved heterogeneity. Comparing the results from these specifications, we find that network effects play a more important role than unobserved heterogeneity in network formation models on Facebook.